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dc.contributor.authorMarini, Simone
dc.contributor.authorAzzurro, Ernesto
dc.contributor.authorCoco, Salvatore
dc.contributor.authorRío Fernandez, Joaquín del
dc.contributor.authorNogueras Cervera, Marc
dc.contributor.authorSbragaglia, Valerio
dc.contributor.authorToma, Daniel
dc.contributor.authorAguzzi, Jacopo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2017-04-27T21:20:55Z
dc.date.available2017-04-27T21:20:55Z
dc.date.issued2016
dc.identifier.citationMarini, S., Azzurro, E., Coco, S., Del Río, J., Nogueras, M., Sbragaglia, V., Toma, D.M., Aguzzi, J. Automatic fish counting from underwater video images: performance estimation and evaluation. A: International Workshop on Marine Technology. "MARTECH 2016: 7th International Workshop on Marine Technology, Barcelona October 26th, 27th and 28th, 2016". Lisbon: 2016, p. 67-70.
dc.identifier.isbn978-84-617-4152-6
dc.identifier.urihttp://hdl.handle.net/2117/103822
dc.description.abstractCabled observatories offer new opportunities to monitor species abundances at frequencies and durations never attained before. When nodes bear cameras, these may be transformed into the first sensor capable of quantifying biological activities at individual, populational, species, and community levels, if automation image processing can be sufficiently implemented. Here, we developed a binary classifier for the fish automated recognition based on Genetic Programming tested on the images provided by OBSEA EMSO testing site platform located at 20 m of depth off Vilanova i la Gertrú (Spain). The performance evaluation of the automatic classifier resulted in a 78% of accuracy compared with the manual counting. Considering the huge dimension of data provided by cabled observatories and the difficulty of manual processing, we consider this result highly promising also in view of future implementation of the methodology to increase the accuracy.
dc.format.extent4 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
dc.subject.lcshFishes -- Counting
dc.subject.lcshFish populations -- Mediterranean Sea
dc.subject.lcshUnderwater imaging systems
dc.subject.lcshOcean bottom -- Research
dc.titleAutomatic fish counting from underwater video images: performance estimation and evaluation
dc.typeConference report
dc.subject.lemacFons marins -- Investigació
dc.subject.lemacComunicacions subacuàtiques
dc.subject.lemacPeixos marins -- Poblacions
dc.contributor.groupUniversitat Politècnica de Catalunya. SARTI - Centre de Desenvolupament Tecnològic de Sistemes d'Adquisició Remota i Tractament de la Informació
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.upc.edu/cdsarti/martech/usb_2016/paginas/articulos_id/id.html
dc.rights.accessOpen Access
local.identifier.drac19528075
dc.description.versionPostprint (published version)
local.citation.authorMarini, S.; Azzurro, E.; Coco, S.; Del Río, J.; Nogueras, M.; Sbragaglia, V.; Toma, D.M.; Aguzzi, J.
local.citation.contributorInternational Workshop on Marine Technology
local.citation.pubplaceLisbon
local.citation.publicationNameMARTECH 2016: 7th International Workshop on Marine Technology, Barcelona October 26th, 27th and 28th, 2016
local.citation.startingPage67
local.citation.endingPage70


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Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain